Multiscale modeling of wear degradation in cylinder liners

Alvaro Moraes, Fabrizio Ruggeri, Raúl Tempone, Pedro Vilanova

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Every mechanical system is naturally subjected to some kind of wear process that, at some point, will cause failure in the system if no monitoring or treatment process is applied. Since failures often lead to high economical costs, it is essential both to predict and to avoid them. To achieve this, a monitoring system of the wear level should be implemented to decrease the risk of failure. In this work, we take a first step into the development of a multiscale indirect inference methodology for state-dependent Markovian pure jump processes. This allows us to model the evolution of the wear level and to identify when the system reaches some critical level that triggers a maintenance response. Since the likelihood function of a discretely observed pure jump process does not have an expression that is simple enough for standard nonsampling optimization methods, we approximate this likelihood by expressions from upscaled models of the data. We use the Master Equation (ME) to assess the goodness-of-fit and to compute the distribution of the hitting time to the critical level.

Original languageEnglish (US)
Pages (from-to)396-409
Number of pages14
JournalMultiscale Modeling and Simulation
Volume12
Issue number1
DOIs
StatePublished - 2014
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Chemistry(all)
  • Modeling and Simulation
  • Ecological Modeling
  • Physics and Astronomy(all)
  • Computer Science Applications

Keywords

  • Indirect inference
  • Master Equation
  • Multiscale approximation
  • Pure jump processes
  • Wear processes

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